This page provides the data published in the Attacks on Health Care Monthly News Brief. For data supporting the Safeguarding Health in Conflict Coalition (SHCC), please see: https://data.humdata.org/dataset/shcchealthcare-dataset
The first dataset '2019 Attacks on Health Care KKADD' covers events where health workers were killed, kidnapped or arrested (KKA) and incidents where health facilities or ambulances were damaged or destroyed by a perpetrator including state and non-state actors, criminals, individuals, students and other staff members so far in 2019.
The remaining datasets include threats and incidents of violence as well as protests and other events affecting health care between September and December 2018.
For a breakdown on the number of health workers killed, kidnapped or arrested (KKA), see In Harms Way dataset.
All data contains incidents identified in open sources. Categorized by country.
Updated October 30, 2019
| Dataset date: Jan 1, 2017-Sep 30, 2019
This dataset updates: Every year
The Safeguarding Health in Conflict Coalition (SHCC) is made up of 40 health provider organizations, humanitarian groups, human rights organizations, NGOs, and academic programs to take action to protect health workers and end attacks against them. This page is managed by SHCC member Insecurity Insight.
Updated June 24, 2019
| Dataset date: Jan 1, 2018-Dec 31, 2018
This dataset updates: As needed
This dataset covers events in which a health facility was damaged or destroyed by explosive weapon use in 2018.
It will be regularly updated with additional details on the impact of explosive weapon use on health facilities. It is a sub-dataset of '2018 SHCC Attacks Data'.
Updated August 29, 2017
| Dataset date: Jan 29, 2016-Aug 4, 2016
This dataset updates: Never
Within 24 hours of the World Health Organization declaring the Zika virus a global health emergency, RIWI began a study in 9 countries across the Americas capturing over 30,000 respondents. Data collection targeted respondents' knowledge of Zika virus transmission mechanisms and confidence in government health agencies to treat and contain the epidemic. The data was collected using RIWI's patented Random Domain Intercept Technology™ (RDIT).
